IEICE TRANSACTIONS on Information
Visual Knowledge Structure Reasoning with Intelligent Topic Map
Summary :
This paper presents a visual knowledge structure reasoning method using Intelligent Topic Map which extends the conventional Topic Map in structure and enhances its reasoning functions. Visual knowledge structure reasoning method integrates two types of knowledge reasoning: the knowledge logical relation reasoning and the knowledge structure reasoning. The knowledge logical relation reasoning implements knowledge consistency checking and the implicit associations reasoning between knowledge points. We propose a Knowledge Unit Circle Search strategy for the knowledge structure reasoning. It implements the semantic implication extension, the semantic relevant extension and the semantic class belonging confirmation. Moreover, the knowledge structure reasoning results are visualized using ITM Toolkit. A prototype system of visual knowledge structure reasoning has been implemented and applied to the massive knowledge organization, management and service for education.
- Publication
- IEICE TRANSACTIONS on Information Vol.E93-D No.10 pp.2805-2812
- Publication Date
- 2010/10/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E93.D.2805
- Type of Manuscript
- PAPER
- Category
- Artificial Intelligence, Data Mining
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Huimin LU, Boqin FENG, Xi CHEN, "Visual Knowledge Structure Reasoning with Intelligent Topic Map" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 10, pp. 2805-2812, October 2010, doi: 10.1587/transinf.E93.D.2805.
Abstract: This paper presents a visual knowledge structure reasoning method using Intelligent Topic Map which extends the conventional Topic Map in structure and enhances its reasoning functions. Visual knowledge structure reasoning method integrates two types of knowledge reasoning: the knowledge logical relation reasoning and the knowledge structure reasoning. The knowledge logical relation reasoning implements knowledge consistency checking and the implicit associations reasoning between knowledge points. We propose a Knowledge Unit Circle Search strategy for the knowledge structure reasoning. It implements the semantic implication extension, the semantic relevant extension and the semantic class belonging confirmation. Moreover, the knowledge structure reasoning results are visualized using ITM Toolkit. A prototype system of visual knowledge structure reasoning has been implemented and applied to the massive knowledge organization, management and service for education.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.2805/_p
Copy
@ARTICLE{e93-d_10_2805,
author={Huimin LU, Boqin FENG, Xi CHEN, },
journal={IEICE TRANSACTIONS on Information},
title={Visual Knowledge Structure Reasoning with Intelligent Topic Map},
year={2010},
volume={E93-D},
number={10},
pages={2805-2812},
abstract={This paper presents a visual knowledge structure reasoning method using Intelligent Topic Map which extends the conventional Topic Map in structure and enhances its reasoning functions. Visual knowledge structure reasoning method integrates two types of knowledge reasoning: the knowledge logical relation reasoning and the knowledge structure reasoning. The knowledge logical relation reasoning implements knowledge consistency checking and the implicit associations reasoning between knowledge points. We propose a Knowledge Unit Circle Search strategy for the knowledge structure reasoning. It implements the semantic implication extension, the semantic relevant extension and the semantic class belonging confirmation. Moreover, the knowledge structure reasoning results are visualized using ITM Toolkit. A prototype system of visual knowledge structure reasoning has been implemented and applied to the massive knowledge organization, management and service for education.},
keywords={},
doi={10.1587/transinf.E93.D.2805},
ISSN={1745-1361},
month={October},}
Copy
TY - JOUR
TI - Visual Knowledge Structure Reasoning with Intelligent Topic Map
T2 - IEICE TRANSACTIONS on Information
SP - 2805
EP - 2812
AU - Huimin LU
AU - Boqin FENG
AU - Xi CHEN
PY - 2010
DO - 10.1587/transinf.E93.D.2805
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 2010
AB - This paper presents a visual knowledge structure reasoning method using Intelligent Topic Map which extends the conventional Topic Map in structure and enhances its reasoning functions. Visual knowledge structure reasoning method integrates two types of knowledge reasoning: the knowledge logical relation reasoning and the knowledge structure reasoning. The knowledge logical relation reasoning implements knowledge consistency checking and the implicit associations reasoning between knowledge points. We propose a Knowledge Unit Circle Search strategy for the knowledge structure reasoning. It implements the semantic implication extension, the semantic relevant extension and the semantic class belonging confirmation. Moreover, the knowledge structure reasoning results are visualized using ITM Toolkit. A prototype system of visual knowledge structure reasoning has been implemented and applied to the massive knowledge organization, management and service for education.
ER -
English
